Gray-world-assumption-based illuminant color estimation using color gamuts with high and low chroma

Harumi Kawamura, Shunichi Yonemura, Jun Ohya, Akira Kojima

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    1 Citation (Scopus)

    Abstract

    A new approach is proposed for estimating illuminant colors from color images under an unknown scene illuminant. The approach is based on a combination of a gray-world-assumption-based illuminant color estimation method and a method using color gamuts. The former method, which is one we had previously proposed, improved on the original method that hypothesizes that the average of all the object colors in a scene is achromatic. Since the original method estimates scene illuminant colors by calculating the average of all the image pixel values, its estimations are incorrect when certain image colors are dominant. Our previous method improves on it by choosing several colors on the basis of an opponent-color property, which is that the average color of opponent colors is achromatic, instead of using all colors. However, it cannot estimate illuminant colors when there are only a few image colors or when the image colors are unevenly distributed in local areas in the color space. The approach we propose in this paper combines our previous method and one using high chroma and low chroma gamuts, which makes it possible to find colors that satisfy the gray world assumption. High chroma gamuts are used for adding appropriate colors to the original image and low chroma gamuts are used for narrowing down illuminant color possibilities. Experimental results obtained using actual images show that even if the image colors are localized in a certain area in the color space, the illuminant colors are accurately estimated, with smaller estimation error average than that generated in the conventional method.

    Original languageEnglish
    Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
    Volume8652
    DOIs
    Publication statusPublished - 2013
    EventColor Imaging XVIII: Displaying, Processing, Hardcopy, and Applications - Burlingame, CA
    Duration: 2013 Feb 42013 Feb 6

    Other

    OtherColor Imaging XVIII: Displaying, Processing, Hardcopy, and Applications
    CityBurlingame, CA
    Period13/2/413/2/6

    Fingerprint

    Color
    color
    Color Image
    Color Space
    Estimation Error
    Estimate
    Pixel
    estimates
    Error analysis
    Unknown
    estimating
    Experimental Results
    Pixels
    pixels

    Keywords

    • blackbody locus
    • color gamut
    • gray world assumption
    • illuminant color estimation

    ASJC Scopus subject areas

    • Applied Mathematics
    • Computer Science Applications
    • Electrical and Electronic Engineering
    • Electronic, Optical and Magnetic Materials
    • Condensed Matter Physics

    Cite this

    Kawamura, H., Yonemura, S., Ohya, J., & Kojima, A. (2013). Gray-world-assumption-based illuminant color estimation using color gamuts with high and low chroma. In Proceedings of SPIE - The International Society for Optical Engineering (Vol. 8652). [86520C] https://doi.org/10.1117/12.2003961

    Gray-world-assumption-based illuminant color estimation using color gamuts with high and low chroma. / Kawamura, Harumi; Yonemura, Shunichi; Ohya, Jun; Kojima, Akira.

    Proceedings of SPIE - The International Society for Optical Engineering. Vol. 8652 2013. 86520C.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Kawamura, H, Yonemura, S, Ohya, J & Kojima, A 2013, Gray-world-assumption-based illuminant color estimation using color gamuts with high and low chroma. in Proceedings of SPIE - The International Society for Optical Engineering. vol. 8652, 86520C, Color Imaging XVIII: Displaying, Processing, Hardcopy, and Applications, Burlingame, CA, 13/2/4. https://doi.org/10.1117/12.2003961
    Kawamura H, Yonemura S, Ohya J, Kojima A. Gray-world-assumption-based illuminant color estimation using color gamuts with high and low chroma. In Proceedings of SPIE - The International Society for Optical Engineering. Vol. 8652. 2013. 86520C https://doi.org/10.1117/12.2003961
    Kawamura, Harumi ; Yonemura, Shunichi ; Ohya, Jun ; Kojima, Akira. / Gray-world-assumption-based illuminant color estimation using color gamuts with high and low chroma. Proceedings of SPIE - The International Society for Optical Engineering. Vol. 8652 2013.
    @inproceedings{77db0201e33f440ca5d69fe324ca31b7,
    title = "Gray-world-assumption-based illuminant color estimation using color gamuts with high and low chroma",
    abstract = "A new approach is proposed for estimating illuminant colors from color images under an unknown scene illuminant. The approach is based on a combination of a gray-world-assumption-based illuminant color estimation method and a method using color gamuts. The former method, which is one we had previously proposed, improved on the original method that hypothesizes that the average of all the object colors in a scene is achromatic. Since the original method estimates scene illuminant colors by calculating the average of all the image pixel values, its estimations are incorrect when certain image colors are dominant. Our previous method improves on it by choosing several colors on the basis of an opponent-color property, which is that the average color of opponent colors is achromatic, instead of using all colors. However, it cannot estimate illuminant colors when there are only a few image colors or when the image colors are unevenly distributed in local areas in the color space. The approach we propose in this paper combines our previous method and one using high chroma and low chroma gamuts, which makes it possible to find colors that satisfy the gray world assumption. High chroma gamuts are used for adding appropriate colors to the original image and low chroma gamuts are used for narrowing down illuminant color possibilities. Experimental results obtained using actual images show that even if the image colors are localized in a certain area in the color space, the illuminant colors are accurately estimated, with smaller estimation error average than that generated in the conventional method.",
    keywords = "blackbody locus, color gamut, gray world assumption, illuminant color estimation",
    author = "Harumi Kawamura and Shunichi Yonemura and Jun Ohya and Akira Kojima",
    year = "2013",
    doi = "10.1117/12.2003961",
    language = "English",
    isbn = "9780819494252",
    volume = "8652",
    booktitle = "Proceedings of SPIE - The International Society for Optical Engineering",

    }

    TY - GEN

    T1 - Gray-world-assumption-based illuminant color estimation using color gamuts with high and low chroma

    AU - Kawamura, Harumi

    AU - Yonemura, Shunichi

    AU - Ohya, Jun

    AU - Kojima, Akira

    PY - 2013

    Y1 - 2013

    N2 - A new approach is proposed for estimating illuminant colors from color images under an unknown scene illuminant. The approach is based on a combination of a gray-world-assumption-based illuminant color estimation method and a method using color gamuts. The former method, which is one we had previously proposed, improved on the original method that hypothesizes that the average of all the object colors in a scene is achromatic. Since the original method estimates scene illuminant colors by calculating the average of all the image pixel values, its estimations are incorrect when certain image colors are dominant. Our previous method improves on it by choosing several colors on the basis of an opponent-color property, which is that the average color of opponent colors is achromatic, instead of using all colors. However, it cannot estimate illuminant colors when there are only a few image colors or when the image colors are unevenly distributed in local areas in the color space. The approach we propose in this paper combines our previous method and one using high chroma and low chroma gamuts, which makes it possible to find colors that satisfy the gray world assumption. High chroma gamuts are used for adding appropriate colors to the original image and low chroma gamuts are used for narrowing down illuminant color possibilities. Experimental results obtained using actual images show that even if the image colors are localized in a certain area in the color space, the illuminant colors are accurately estimated, with smaller estimation error average than that generated in the conventional method.

    AB - A new approach is proposed for estimating illuminant colors from color images under an unknown scene illuminant. The approach is based on a combination of a gray-world-assumption-based illuminant color estimation method and a method using color gamuts. The former method, which is one we had previously proposed, improved on the original method that hypothesizes that the average of all the object colors in a scene is achromatic. Since the original method estimates scene illuminant colors by calculating the average of all the image pixel values, its estimations are incorrect when certain image colors are dominant. Our previous method improves on it by choosing several colors on the basis of an opponent-color property, which is that the average color of opponent colors is achromatic, instead of using all colors. However, it cannot estimate illuminant colors when there are only a few image colors or when the image colors are unevenly distributed in local areas in the color space. The approach we propose in this paper combines our previous method and one using high chroma and low chroma gamuts, which makes it possible to find colors that satisfy the gray world assumption. High chroma gamuts are used for adding appropriate colors to the original image and low chroma gamuts are used for narrowing down illuminant color possibilities. Experimental results obtained using actual images show that even if the image colors are localized in a certain area in the color space, the illuminant colors are accurately estimated, with smaller estimation error average than that generated in the conventional method.

    KW - blackbody locus

    KW - color gamut

    KW - gray world assumption

    KW - illuminant color estimation

    UR - http://www.scopus.com/inward/record.url?scp=84875862054&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=84875862054&partnerID=8YFLogxK

    U2 - 10.1117/12.2003961

    DO - 10.1117/12.2003961

    M3 - Conference contribution

    AN - SCOPUS:84875862054

    SN - 9780819494252

    VL - 8652

    BT - Proceedings of SPIE - The International Society for Optical Engineering

    ER -